Lecture Notes in Artificial Intelligence 2702Edited by J. G. Carbonell and J. Siekmann

Subseries of Lecture Notes in Computer Science

3BerlinHeidelbergNew YorkHong KongLondonMilanParisTokyo

Peter Brusilovsky Albert CorbettFiorella de Rosis (Eds.)

User Modeling2003

9th International Conference, UM 2003Johnstown, PA, USA, June 22-26, 2003Proceedings

1 3

Series Editors

Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USAJorg Siekmann, University of Saarland, Saarbrucken, Germany

Volume Editors

Peter BrusilovskyUniversity of PittsburghSchool of Information SciencesDepartment of Information Science and Telecommunications135 North Bellefield Avenue, Pittsburgh, PA 15260, USAE-mail: peterb@mail.sis.pitt.edu

Albert CorbettCarnegie Mellon UniversityHuman Computer Interaction InstitutePittsburgh, PA 15213, USAE-mail: corbett+@cmu.edu

Fiorella de RosisUniversity of BariIntelligent InterfacesDepartment of InformaticsVia Orabona 4, 70126 Bari, ItalyE-mail: derosis@di.uniba.it

Cataloging-in-Publication Data applied for

A catalog record for this book is available from the Library of Congress.

Bibliographic information published by Die Deutsche BibliothekDie Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie;detailed bibliographic data is available in the Internet at <http://dnb.ddb.de>.

CR Subject Classification (1998): H.5.2, I.2, H.5, H.4, I.6, J.4, J.5, K.4, K.6

ISSN 0302-9743ISBN 3-540-40381-7 Springer-Verlag Berlin Heidelberg New York

This work is subject to copyright. All rights are reserved, whether the whole or part of the material isconcerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting,reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publicationor parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965,in its current version, and permission for use must always be obtained from Springer-Verlag. Violations areliable for prosecution under the German Copyright Law.

Springer-Verlag Berlin Heidelberg New Yorka member of BertelsmannSpringer Science+Business Media GmbH

http://www.springer.de

© Springer-Verlag Berlin Heidelberg 2003Printed in Germany

Typesetting: Camera-ready by author, data conversion by PTP-Berlin GmbHPrinted on acid-free paper SPIN: 10928677 06/3142 5 4 3 2 1 0

Preface

The International User Modeling Conferences are the events at which researchfoundations are being laid for the personalization of computer systems. In the last 15years, the field of user modeling has produced significant new theories and methods toanalyze and model computer users in short- and long-term interactions. A user modelis an explicit representation of properties of individual users or user classes. It allowsthe system to adapt its performance to user needs and preferences. Methods forpersonalizing human-computer interaction based on user models have beensuccessfully developed and applied in a number of domains, such as informationfiltering, adaptive natural language and hypermedia presentation, tutoring systems, e-commerce and medicine. There is also a growing recognition of the need to evaluatethe results of new user modeling methods and prototypes in empirical studies and agrowing focus on evaluation methods.

New trends in HCI create new and interesting challenges for user modeling. Whileconsolidating results in traditional domains of interest, the user modeling field nowalso addresses problems of personalized interaction in mobile and ubiquitouscomputing and adaptation to user attitudes and affective states. Finally, with thespread of user modeling in everyday applications and on the Web, new concerns aboutprivacy preservation are emerging.

All these topics are covered in the proceedings of UM 2003, the 9th InternationalConference on User Modeling. This is the latest in a conference series begun in 1986,and follows recent meetings in Sonthofen (2001), Banff (1999), Sardinia (1997),Hawaii (1996) and Cape Cod (1994). Previous successes in user modeling researchreflect the cooperation of researchers in different fields, including artificialintelligence, human-computer interaction, education, cognitive psychology andlinguistics. User Modeling 2003 followed the tradition of the earlier International UserModeling Conferences in providing a forum in which researchers and practitionerswith different backgrounds can exchange their complementary insights.

The UM 2003 conference included 3 invited talks, 26 full paper presentations, 28poster presentations, 9 doctoral consortium presentations, 7 workshops and 2 tutorials.The full text of all presented papers appear in these proceedings, along withsummaries of the posters and doctoral consortium papers and abstracts of the invitedtalks. UM 2003 received 106 submissions to the main technical program from 24countries. The selection criteria were stringent, and the 24.5% acceptance rate for fullpapers is quite typical for the User Modeling series and its traditional approach toassembling a high-quality technical program. The following list provides thedistribution of all submissions accepted for the technical program (papers, posters anddoctoral consortium papers) by region of origin: Australia and New Zealand (6),Canada and USA (28), Europe and Israel (28), and Japan (1).

The three invited talks provided insights across a broad range of user modeling issues:

- Adaptive Interfaces for Ubiquitous Web Access, by Michael Pazzani;- Computers That Recognize and Respond to User Emotion, by Rosalind Picard;- The Advantages of Explicitly Representing Problem Spaces, by Kurt VanLehn.

VI Preface

In addition to the contributions featured in this volume, UM 2003 offered twotutorials:

- Evaluating the Effectiveness of User Models by Experiments, presented by DavidChin;

- Systems That Adapt to Their Users: An Integrative Overview, presented byAnthony Jameson.

Seven workshops form the final major component of UM 2003. Their proceedingscan be accessed via http://www.um.org, the website of User Modeling, Inc. Theworkshop topics were:

- Workshop on Adaptive Hypermedia and Adaptive Web-Based Systems, organizedby Paul De Bra and Judy Kay;

- 3rd Workshop on Assessing and Adapting to User Attitudes and Affect: Why,When and How?, organized by Cristina Conati, Eva Hudlicka and ChristineLisetti;

- 2nd Workshop on Empirical Evaluation of Adaptive Systems, organized byStephan Weibelzahl and Alexandros Paramythis;

- MLIRUM 2003: 2nd Workshop on Machine Learning, Information Retrieval andUser Modeling, organized by Sofus Macskassy, Ross Wilkinson, Ayse Goker andMathias Bauer;

- TV 2003: 3rd Workshop on Personalization in Future TV, organized by LilianaArdissono and Mark Maybury;

- Workshop on User and Group Models for Web-Based Adaptive CollaborativeEnvironments, organized by Jesús Boticario, Elena Gaudioso, Mathias Bauer andGal Kaminka; and

- Workshop on User Modelling for Ubiquitous Computing, organized by KeithCheverst, Berardina Nadja De Carolis and Antonio Krüger.

UM 2003 was hosted by the University of Pittsburgh under the auspices of UserModeling, Inc.

We hope that these proceedings will be a useful support both in discussingpresentations at the conference and in communicating advances in the domain to thosewho were unable to attend. Organizing a conference is many months of work, whichmay make differences among the chairs emerge. In our case, harmonic and friendlysharing of duties was the principle and practice of our work.

Acknowledgements

A great many people contributed to the high quality of this conference. We owespecial thanks to the members of the Program Committee for their unstinting efforts inreviewing the paper and poster submissions, selecting the winners of the best paperawards, and selecting the invited speakers.

David Albrecht, AustraliaLiliana Ardissono, ItalyMathias Bauer, GermanySandra Carberry, USANoelle Carbonell, FranceKeith Cheverst, UKDavid Chin, USACristina Conati, CanadaPiotr Gmytrasiewicz, USABrad Goodman, USAHaym Hirsh, USAKristina Höök, SwedenEric Horvitz, USAAnthony Jameson, GermanyJudy Kay, Australia

Alfred Kobsa, USA

Antonio Krüger, GermanyDiane Litman, USAGordon McCalla, CanadaKathleen McCoy, USAAntonija Mitrovic, NewZealandRiichiro Mizoguchi, JapanHelen Pain, UKCécile Paris, AustraliaBarry Smyth, IrelandConstantine Stephanidis,GreeceCarlo Tasso, ItalyJulita Vassileva, CanadaGerhard Weber, GermanyIngrid Zukerman, Australia

We also thank the external reviewers:

Mitsuru IkedaAkiko InabaCarl Kadie

Akihiro KashiharaFrank Wittig

The Doctoral Consortium program was co-chaired by Sandra Carberry, USA andCristina Conati, Canada. They were assisted by the following committee:

Joseph Beck, USASusan Bull, UKGiuseppe Carenini, CanadaAbigail Gertner, USAJames Greer, CanadaEva Hudlicka, USANeal Lesh, USA

Frank Linton, USAChristine Lisetti, USALisa Michaud, USAEva Millán, SpainTanja Mitrovic, New ZealandJack Mostow, USAKurt VanLehn, USA

Frank Wittig and Anthony Jameson, Germany co-chaired the efforts of the workshoporganizers:

Liliana Ardissono, ItalyMathias Bauer, Germany

Jesus Boticario, SpainKeith Cheverst, UK

VIII Acknowledgements

Cristina Conati, CanadaPaul DeBra, The NetherlandsBerardina Nadja De Carolis,ItalyElena Gaudioso, SpainAyse Goker, UKEva Hudlicka, USAGal Kaminka, USAJudy Kay, AustraliaAntonio Krüger, Germany

Christine Lisetti, USASofus Macskassy, USAMark Maybury, USAAlexandros Paramythis,AustriaStephan Weibelzahl,GermanyRoss Wilkinson, Australia

We also extend our thanks to

- The Local Advisory Committee, Jack Mostow, Christian Lebiere and KenKoedinger;

- The Publicity Chair, Ayse Goker;- Sergey Sosnosvsky for maintaining the conference website;- Valeria Carofiglio, Angela Wagner and Mary Scott for helping us in managing

the submissions and producing the proceedings;- Susan Strauss Williams and Heather Frye for their assistance with financial

planning and arrangements.

Special thanks to Julita Vassileva, Mathias Bauer and Anthony Jameson for helping toinsure a continuity in the UM organization and for assisting with suggestions incritical situations.

Generous financial support provided by Microsoft Research made it possible forseveral doctoral students to attend the conference. And we are grateful to both KluwerAcademic Publishers for sponsoring the best paper award and to the James Chenfamily for sponsoring best student paper awards.

April 2003 Peter BrusilovskyAlbert Corbett

Fiorella de Rosis

Table of Contents

Abstracts of Invited Talks

Adaptive Interfaces for Ubiquitous Web Access . . . . . . . . . . . . . . . . . . . . . . . 1Michael Pazzani

Computers That Recognize and Respond to User Emotion . . . . . . . . . . . . . 2Rosalind Picard

The Advantages of Explicitly Representing Problem Spaces . . . . . . . . . . . . 3Kurt VanLehn

Adaptive Hypermedia

The Three Layers of Adaptation Granularity . . . . . . . . . . . . . . . . . . . . . . . . . 4Alexandra Cristea, Licia Calvi

Adaptive Presentation of Multimedia Interface Case Study: “BrainStory” Course . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Halima Habieb-Mammar, Franck Tarpin-Bernard, Patrick Prevot

Discovering Prediction Rules in AHA! Courses . . . . . . . . . . . . . . . . . . . . . . . . 25Cristobal Romero, Sebastian Ventura, Paul de Bra, Carlos de Castro

Adaptive Web

Word Weighting Based on User’s Browsing History . . . . . . . . . . . . . . . . . . . 35Yutaka Matsuo

SNIF-ACT: A Model of Information Foraging on the World Wide Web . . 45Peter Pirolli, Wai-Tat Fu

Adapting to the User’s Internet Search Strategy . . . . . . . . . . . . . . . . . . . . . . 55Jean-David Ruvini

Learning a Model of a Web User’s Interests . . . . . . . . . . . . . . . . . . . . . . . . . . 65Tingshao Zhu, Russ Greiner, Gerald Haubl

Modelling Users’ Interests and Needs for an Adaptive OnlineInformation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Enrique Alfonseca, Pilar Rodrıguez

Declarative Specifications for Adaptive Hypermedia Based on aSemantic Web Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Serge Garlatti, Sebastien Iksal

X Table of Contents

Natural Language and Dialog

Emotional Dialogs with an Embodied Agent . . . . . . . . . . . . . . . . . . . . . . . . . 86Addolorata Cavalluzzi, Berardina De Carolis, Valeria Carofiglio,Giuseppe Grassano

Evaluating a Model to Disambiguate Natural Language Parses on theBasis of User Language Proficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

Lisa N. Michaud, Kathleen F. McCoy

Incorporating a User Model into an Information TheoreticFramework for Argument Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Ingrid Zukerman, Sarah George, Mark George

Using Dialogue Games to Maintain Diagnostic Interactions . . . . . . . . . . . . . 117Vania Dimitrova

Plan Recognition

Extending Plan Inference Techniques to Recognize Intentions inInformation Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

Stephanie Elzer, Nancy Green, Sandra Carberry, Kathleen F. McCoy

Leveraging Collaborative Effort to Infer Intent . . . . . . . . . . . . . . . . . . . . . . . . 133Joshua Introne, Richard Alterman

Plan Recognition to Aid the Visually Impaired . . . . . . . . . . . . . . . . . . . . . . . 138Marcus J. Huber, Richard Simpson

Evaluation

Performance Evaluation of User Modeling Servers under Real-WorldWorkload Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143

Alfred Kobsa, Josef Fink

Evaluating the Inference Mechanism of Adaptive Learning Systems . . . . . 154Stephan Weibelzahl, Gerhard Weber

The Continuous Empirical Evaluation Approach: Evaluating AdaptiveWeb-Based Courses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

Alvaro Ortigosa, Rosa M. Carro

Emerging Issues of User Modeling

Privacy Preservation Improvement by Learning Optimal ProfileGeneration Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Tsvi Kuflik, Bracha Shapira, Yuval Elovici, Adlai Maschiach

Interfaces for Eliciting New User Preferences in Recommender Systems . . 178Sean M. McNee, Shyong K. Lam, Joseph A. Konstan, John Riedl

Table of Contents XI

Modeling Multitasking Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188Malcolm Slaney, Jayashree Subrahmonia, Paul Maglio

VlUM , a Web-Based Visualisation of Large User Models . . . . . . . . . . . . . . 198James Uther, Judy Kay

A Multiagent Approach to Obtain Open and Flexible User Models inAdaptive Learning Communities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203

Felix Hernandez, Elena Gaudioso, Jesus G. Boticario

A Model for Integrating an Adaptive Information Filter UtilizingBiosensor Data to Assess Cognitive Load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208

Curtis S. Ikehara, David N. Chin, Martha E. Crosby

Ontology-Based User Modeling for Knowledge Management Systems . . . . 213Liana Razmerita, Albert Angehrn, Alexander Maedche

Group Modeling and Cooperation

Motivating Cooperation on Peer to Peer Networks . . . . . . . . . . . . . . . . . . . . 218Helen Bretzke, Julita Vassileva

Discourse Analysis Techniques for Modeling Group Interaction . . . . . . . . . 228Alexander Feinman, Richard Alterman

Group Decision Making through Mediated Discussions . . . . . . . . . . . . . . . . 238Daniel Kudenko, Mathias Bauer, Dietmar Dengler

Modeling Task-Oriented Discussion Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . 248Roy Wilson

Modeling the Multiple People That Are Me . . . . . . . . . . . . . . . . . . . . . . . . . . 258Judith Masthoff

Applications

Iems: Helping Users Manage Email . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263Eric McCreath, Judy Kay

Modelling Reputation in Agent-Based Marketplaces to Improve thePerformance of Buying Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

Thomas Tran, Robin Cohen

Customising the Interaction with Configuration Systems . . . . . . . . . . . . . . 283Liliana Ardissono, Anna Goy, Matt Holland, Giovanna Petrone,Ralph Schafer

Does Adapted Information Help Patients with Cancer? . . . . . . . . . . . . . . . . 288Diana Bental, Alison Cawsey, Janne Pearson, Ray Jones

XII Table of Contents

Empirical Evaluation of Adaptive User Modeling in a MedicalInformation Retrieval Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292

Eugene Santos, Hien Nguyen, Qunhua Zhao, Erik Pukinskis

Multivariate Preference Models and Decision Making with theMAUT Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297

Christian Schmitt, Dietmar Dengler, Mathias Bauer

Student Modeling Methods

Predicting Student Help-Request Behavior in an Intelligent Tutorfor Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303

Joseph E. Beck, Peng Jia, June Sison, Jack Mostow

A Comparative Analysis of Cognitive Tutoring andConstraint-Based Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313

Antonija Mitrovic, Kenneth R. Koedinger, Brent Martin

Assessing Student Proficiency in a Reading Tutor That Listens . . . . . . . . . 323Joseph E. Beck, Peng Jia, Jack Mostow

Adaptive Bayes for a Student Modeling Prediction Task Based onLearning Styles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

Gladys Castillo, Joao Gama, Ana M. Breda

User Modeling and Problem-Space Representation in the TutorRuntime Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Steven Ritter, Stephen Blessing, Leslie Wheeler

A Neuro-fuzzy Approach in Student Modeling . . . . . . . . . . . . . . . . . . . . . . . . 337Regina Stathacopoulou, Maria Grigoriadou, George D. Magoulas,Denis Mitropoulos

Learning Environments: Natural Language andPedagogy

Student Modeling for an Intelligent Agent in a CollaborativeLearning Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342

Frank Linton, Bradley Goodman, R. Gaimari, J. Zarrella, Helen Ross

A Teaching Model Exploiting Cognitive Conflict Driven by aBayesian Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

K. Stacey, E. Sonenberg, A. Nicholson, T. Boneh, V. Steinle

Towards Intelligent Agents for Collaborative Learning:Recognizing the Roles of Dialogue Participants . . . . . . . . . . . . . . . . . . . . . . . 363

Bradley Goodman, Janet Hitzeman, Frank Linton, Helen Ross

Table of Contents XIII

Modeling Student Performance to Enhance the Pedagogy of AutoTutor . . 368Tanner Jackson, Eric Mathews, King-Ip Lin, Andrew Olney,Art Graesser

Modeling Hinting Strategies for Geometry Theorem Proving . . . . . . . . . . . . 373Noboru Matsuda, Kurt VanLehn

Mobile and Ubiquitous Computing

User Modelling in the Car . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378Niels Ole Bernsen

User Modelling and Mobile Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383Susan Bull

D-ME: Personal Interaction in Smart Environments . . . . . . . . . . . . . . . . . . . 388Berardina De Carolis, Sebastiano Pizzutilo, Ignazio Palmisano

A User Modeling Markup Language (UserML) forUbiquitous Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

Dominik Heckmann, Antonio Krueger

Purpose-Based User Modelling in a Multi-agent PortfolioManagement System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398

Xiaolin Niu, Gordon McCalla, Julita Vassileva

User Modeling in Adaptive Audio-Augmented Museum Environments . . . 403Andreas Zimmermann, Andreas Lorenz, Marcus Specht

Doctoral Consortium Papers

MAPS: Dynamic Scaffolding for Independence for Persons withCognitive Impairments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408

Stefan Carmien

Adaptations of Multimodal Content in Dialog Systems TargetingHeterogeneous Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411

Songsak Channarukul

Learning Knowledge Rich User Models from the Semantic Web . . . . . . . . 414Gunnar Astrand Grimnes

Modeling User Navigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417Eelco Herder

A Longitudinal, Naturalistic Study of Information Search & UseBehavior as Implicit Feedback for User ModelConstruction & Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420

Diane Kelly

XIV Table of Contents

Facilitating the Comprehension of Online Learning Courses withAdaptivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423

Stefan Lippitsch

Scrutable User Models in Decentralised Adaptive Systems . . . . . . . . . . . . . . 426Andrew Lum

A Pseudo-Supervised Approach to Improve a RecommenderBased on Collaborative Filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429

Jose D. Martın-Guerrero

Visualizing a User Model for Educational Adaptive Information Retrieval 432Swantje Willms

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435